Lung Adenocarcinoma Cases Research Articles

Applying PET-CT for predicting the efficacy of SBRT to inoperable early-stage lung adenocarcinoma: A Brazilian case-series

Stereotactic body radiotherapy (SBRT) is a treatment option for early-stage inoperable primary lung cancer. Here we report a thorough description of the prognostic value of pre-SBRT SUVmax for predicting the efficacy of SBRT in early-stage lung adenocarcinoma. This is a retrospective study of consecutive cases of early-stage inoperable lung adenocarcinoma, staged with PET-CT, treated with SBRT between 2007 and 17. Kaplan-Meier (KM) curves were used to assess overall survival and compare time to event between those with PET-CT SUVmax values ≤5.0 and those >5. Fisher's Exact tests and the Mann-Whitney U were used to compare the patient and clinical data of those with SUVmax≤5.0 and >5.0, and those with and without any failure. Amongst 50 lung carcinoma lesions, from 47 patients (34 (68%)-T1a or <T1b), estimated median overall survival from the KM was 44.9 months (95% confidence interval 35.5-54.3). Five experienced a local failure, which was inadequate for detecting differences between those with PET-CT SUVmax ≤5.0 and those >5 (p=0.112). In addition, 5 experienced a regional failure and 4 a distant failure. Higher PET-CT SUVmax values before SBRT were associated with an increased risk of any failure (36% versus 0%, p=0.0040 on Fisher's Exact test) and faster time to event (p=0.010, log rank test). Both acute and late toxicities profile were acceptable. Patients with early-stage inoperable lung adenocarcinoma present good clinical outcomes when treated with SBRT. We raised the hypothesis that the value of PET-CT SUVmax before SBRT may be an important predictive factor in disease control. None.

An immune-related nomogram model that predicts the overall survival of patients with lung adenocarcinoma

BackgroundLung adenocarcinoma accounts for approximately 40% of all primary lung cancers; however, the mortality rates remain high. Successfully predicting progression and overall (OS) time will provide clinicians with more options to manage this disease.MethodsWe analyzed RNA sequencing data from 510 cases of lung adenocarcinoma from The Cancer Genome Atlas database using CIBERSORT, ImmuCellAI, and ESTIMATE algorithms. Through these data we constructed 6 immune subtypes and then compared the difference of OS, immune infiltration level and gene expression between these immune subtypes. Also, all the subtypes and immune cells infiltration level were used to evaluate the relationship with prognosis and we introduced lasso-cox method to constructe an immune-related prognosis model. Finally we validated this model in another independent cohort.ResultsThe C3 immune subtype of lung adenocarcinoma exhibited longer survival, whereas the C1 subtype was associated with a higher mutation rate of MUC17 and FLG genes compared with other subtypes. A multifactorial correlation analysis revealed that immune cell infiltration was closely associated with overall survival. Using data from 510 cases, we constructed a nomogram prediction model composed of clinicopathologic factors and immune signatures. This model produced a C-index of 0.73 and achieved a C-index of 0.844 using a validation set.ConclusionsThrough this study we constructed an immune related prognosis model to instruct lung adenocarcinoma’s OS and validated its value in another independent cohost. These results will be useful in guiding treatment for lung adenocarcinoma based on tumor immune profiles.

Comprehensive molecular analysis of a four-pyroptosis-gene signature with prognosis and immune landscape in lung adenocarcinoma

Pyroptosis plays an important role in tumor immunity. However, the biological behavior and prognostic significance of pyroptosis remain unclear. We identified 41 pyroptosis regulators differently expressed in lung adenocarcinoma (LUAD). All cases of LUAD can be classified into two molecular subtypes using unsupervised clustering algorithm. Using multiple analyses, a four-pyroptosis-gene signature was constructed, and all LUAD patients were categorized as low-risk or high-risk with a longer overall survival (OS) time in the low-risk group(P < 0.001). This signature had power prognosis and stratification which was validated by six independent datasets and clinical subtypes. Besides, this signature showed distinct clinical outcomes, immune landscapes in different risk groups. Moreover, the low-risk group had a higher response against immunotherapy with a lower TIDE score. Importantly, this signature surpassed other biomarkers (TIDE, TMB, PD-L1) in predicting prognosis. Overall, the current study might help with precise prognostic prediction and crucial treatment strategies, eventually promoting tailored therapy for LUAD patients.

NSCLC Subtyping in Conventional Cytology: Results of the International Association for the Study of Lung Cancer Cytology Working Group Survey to Determine Specific Cytomorphologic Criteria for Adenocarcinoma and Squamous Cell Carcinoma

IntroductionAccurate subtyping of NSCLC into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is the cornerstone of NSCLC diagnosis. Cytology samples reveal higher rates of classification failures, that is, subtyping as non–small cell carcinoma—not otherwise specified (NSCC-NOS), as compared with histology specimens. This study aims to identify specific algorithms on the basis of known cytomorphologic features that aid accurate and successful subtyping of NSCLC on cytology. MethodsA total of 13 expert cytopathologists participated anonymously in an online survey to subtype 119 NSCLC cytology cases (gold standard diagnoses being LUAD in 80 and LUSC in 39) enriched for nonkeratinizing LUSC. They selected from 23 predefined cytomorphologic features that they used in subtyping. Data were analyzed using machine learning algorithms on the basis of random forest method and regression trees. ResultsFrom 1474 responses recorded, concordant cytology typing was achieved in 53.7% (792 of 1474) responses. NSCC-NOS rates on cytology were similar among gold standard LUAD (36%) and LUSC (38%) cases. Misclassification rates were higher in gold standard LUSC (17.6%) than gold standard LUAD (5.5%; p < 0.0001). Keratinization, when present, recognized LUSC with high accuracy. In its absence, the machine learning algorithms developed on the basis of experts’ choices were unable to reduce cytology NSCC-NOS rates without increasing misclassification rates. ConclusionsSuboptimal recognition of LUSC in the absence of keratinization remains the major hurdle in improving cytology subtyping accuracy with such cases either failing classification (NSCC-NOS) or misclassifying as LUAD. NSCC-NOS seems to be an inevitable morphologic diagnosis emphasizing that ancillary immunochemistry is necessary to achieve accurate subtyping on cytology.

A case of left upper lobe lung adenocarcinoma with left mediastinal A5+A9-10 pulmonary artery undergoing complete video-assisted thoracic surgery

A case of left upper lobe lung adenocarcinoma with left mediastinal A5+A9-10 pulmonary artery undergoing complete video-assisted thoracic surgery

MET Exon 14 Splice-Site Mutations Preferentially Activate KRAS Signaling to Drive Tumourigenesis.

Simple SummaryMET exon 14 splice-site mutations occur in ~3–4% of lung adenocarcinoma cases, defining a cohort of patients which might benefit from anti-MET targeted therapy. Such therapies have yielded mixed results, however, pointing to the need for better treatment design. Our study sought to aid this by characterizing key changes in mutant MET signaling behaviour. We first compared the transcriptional profiles of lung tumours with either METΔex14 or wild-type MET-amplification. METΔex14-mutant tumours exhibited increased activation of the Ras-MAPK pathway, consistent with our observations in an isogenic model system. Furthermore, sustained activity of this pathway is necessary for proliferation and maintenance of METΔex14 tumours, while forced reactivation of this pathway is sufficient to restore growth in the absence of MET activity. Our findings suggest that the MAPK pathway represents a main effector of METΔex14-driven cancer, lending credence to the possibility of combined MET-MAPK inhibition to improve therapeutic outcomes.Targeted therapies for MET exon 14-skipping (METΔex14)-driven lung cancers have generated some promising results but response rates remain below that seen for other kinase-driven cancers. One strategy for improving treatment outcomes is to employ rational combination therapies to enhance the suppression of tumour growth and delay or prevent the emergence of resistance. To this end, we profiled the transcriptomes of MET-addicted lung tumours and cell lines and identified the RAS-mitogen-activated protein kinase (MAPK) pathway as a critical effector required for METΔex14-dependent growth. Ectopic expression of MET in an isogenic cell line model showed that overexpression of the mutant MET receptor led to higher levels of MAPK phosphorylation and nuclear import, resulting in increased expression and phosphorylation of nuclear MAPK targets. In comparison, other known MET effectors were unaffected. Inhibition of this pathway by KRAS knockdown in MET-addicted cells in vitro led to decreased viability in only the METΔex14-mutant cells. Conversely, decoupling RAS-MAPK axis, but not other effector pathways, from MET activity via the introduction of constitutively active mutants conferred resistance to MET inhibitors in vitro. Our results suggest that aberrant hyperactivity of the MET receptor caused by the exon 14-skipping mutation does not uniformly upregulate all known downstream effectors, rather gaining a predilection for aberrantly activating and subsequently relying on the RAS-MAPK pathway. These findings provide a rationale for the co-targeting of the RAS-MAPK pathway alongside MET to prolong therapeutic response and circumvent resistance to improve patient survival.

Integrative Predictive Models of Computed Tomography Texture Parameters and Hematological Parameters for Lymph Node Metastasis in Lung Adenocarcinomas.

ObjectivesThe aims of the study were to integrate characteristics of computed tomography (CT), texture, and hematological parameters and to establish predictive models for lymph node (LN) metastasis in lung adenocarcinoma.MethodsA total of 207 lung adenocarcinoma cases with confirmed postoperative pathology and preoperative CT scans between February 2017 and April 2019 were included in this retrospective study. All patients were divided into training and 2 validation cohorts chronologically in the ratio of 3:1:1. The χ2 test or Fisher exact test were used for categorical variables. The Shapiro-Wilk test and Mann-Whitney U test were used for continuous variables. Logistic regression and machine learning algorithm models based on CT characteristics, texture, and hematological parameters were used to predict LN metastasis. The performance of the multivariate models was evaluated using a receiver operating characteristic curve; prediction performance was evaluated in the validation cohorts. Decision curve analysis confirmed its clinical utility.ResultsLogistic regression analysis demonstrated that pleural thickening (P = 0.013), percentile 25th (P = 0.033), entropy gray-level co-occurrence matrix 10 (P = 0.019), red blood cell distribution width (P = 0.012), and lymphocyte-to-monocyte ratio (P = 0.049) were independent risk factors associated with LN metastasis. The area under the curve of the predictive model established using the previously mentioned 5 independent risk factors was 0.929 in the receiver operating characteristic analysis. The highest area under the curve was obtained in the training cohort (0.777 using Naive Bayes algorithm).ConclusionsIntegrative predictive models of CT characteristics, texture, and hematological parameters could predict LN metastasis in lung adenocarcinomas. These findings may provide a reference for clinical decision making.

Establishing a Macrophage Phenotypic Switch-Associated Signature-Based Risk Model for Predicting the Prognoses of Lung Adenocarcinoma.

BackgroundTumor-associated macrophages are important components of the tumor microenvironment, and the macrophage phenotypic switch has been shown to correlate with tumor development. However, the use of a macrophage phenotypic switch-related gene (MRG)-based prognosis signature for lung adenocarcinoma (LADC) has not yet been investigated.MethodsIn total, 1,114 LADC cases from two different databases were collected. The samples from TCGA were used as the training set (N = 490), whereas two independent datasets (GSE31210 and GSE72094) from the GEO database were used as the validation sets (N = 624). A robust MRG signature that predicted clinical outcomes of LADC patients was identified through multivariate COX and Lasso regression analysis. Gene set enrichment analysis was applied to analyze molecular pathways associated with the MRG signature. Moreover, the fractions of 22 immune cells were estimated using CIBERSORT algorithm.ResultsAn eight MRG-based signature comprising CTSL, ECT2, HCFC2, HNRNPK, LRIG1, OSBPL5, P4HA1, and TUBA4A was used to estimate the LADC patients’ overall survival. The MRG model was capable of distinguishing high-risk patients from low-risk patients and accurately predict survival in both the training and validation cohorts. Subsequently, the eight MRG-based signature and other features were used to construct a nomogram to better predict the survival of LADC patients. Calibration plots and decision curve analysis exhibited good consistency between the nomogram predictions and actual observation. ROC curves displayed that the signature had good robustness to predict LADC patients’ prognostic outcome.ConclusionsWe identified a phenotypic switch-related signature for predicting the survival of patients with LADC.

Different clinical significance of novel B7 family checkpoints VISTA and HHLA2 in human lung adenocarcinoma.

Background: VISTA and HHLA2 are two recently identified members of the B7 homologue family of immune-regulatory molecules. But the expression patterns and clinical significance of VISTA and HHLA2 in lung adenocarcinoma (LUAD) remain largely unknown. Methods: Immunohistochemistry was performed to examine the expression of VISTA, HHLA2, PD-L1 and CD8+ tumor-infiltrating lymphocytes in 74 cases of LUAD. The expression of VISTA, HHLA2, PD-L1, CD68 and CD8 proteins was detected by multiplex immunofluorescence staining in the LUAD tissues. Results: High expression of VISTA and HHLA2 was observed in LUAD compared with noncancerous tissues. High VISTA expression in immune cells predicted a high mortality rate and worse survival. Conclusion: VISTA and HHLA2 are potential immunotherapeutic targets that possess different prognostic significance in LUAD.

Indoor Air Pollution Increases the Risk of Lung Cancer.

(1) Background: Cooking and burning incense are important sources of indoor air pollutants. No studies have provided biological evidence of air pollutants in the lungs to support this association. Analysis of pleural fluid may be used to measure the internal exposure dose of air pollutants in the lung. The objective of this study was to provide biological evidence of indoor air pollutants and estimate their risk of lung cancer. (2) Methods: We analyzed 14 common air pollutants in the pleural fluid of 39 cases of lung adenocarcinoma and 40 nonmalignant controls by gas chromatography-mass spectrometry. (3) Results: When we excluded the current smokers and adjusted for age, the adjusted odds ratios (ORs) were 2.22 (95% confidence interval CI = 0.77–6.44) for habitual cooking at home and 3.05 (95% CI = 1.06–8.84) for indoor incense burning. In females, the adjusted ORs were 5.39 (95% CI = 1.11–26.20) for habitual cooking at home and 6.01 (95% CI = 1.14–31.66) for indoor incense burning. In pleural fluid, the most important exposure biomarkers for lung cancer were naphthalene, ethylbenzene, and o-xylene. (4) Conclusions: Habitual cooking and indoor incense burning increased the risk of lung adenocarcinoma.

BACH1: A Potential Predictor of Survival in Early-Stage Lung Adenocarcinoma.

Purpose Recent researches showed the vital role of BACH1 in promoting the metastasis of lung cancer. We aimed to explore the value of BACH1 in predicting the overall survival (OS) of early-stage (stages I-II) lung adenocarcinoma. Patients and Methods. Lung adenocarcinoma cases were screened from the Cancer Genome Atlas (TCGA) database. Functional enrichment analysis was performed to obtain the biological mechanisms of BACH1. Gene set enrichment analysis (GSEA) was performed to identify the difference of biological pathways between high- and low-BACH1 groups. Univariate and multivariate COX regression analysis had been used to screen prognostic factors, which were used to establish the BACH1 expression-based prognostic model in the TCGA dataset. The C-index and time-dependent AUC curve were used to evaluate predictive power of the model. External validation of prognostic value was performed in two independent datasets from Gene Expression Omnibus (GEO). Decision analysis curve was finally used to evaluate clinical usefulness of the BACH1-based model beyond pathologic stage alone. Results BACH1 was an independent prognostic factor for lung adenocarcinoma. High-expression BACH1 cases had worse OS. BACH1-based prognostic model showed an ideal C-index and t-AUC and validated by two GEO datasets, independently. More importantly, the BACH1-based model indicated positive clinical applicability by DCA curves. Conclusion Our research confirmed that BACH1 was an important predictor of prognosis in early-stage lung adenocarcinoma. The higher the expression of BACH1, the worse OS of the patients.

A Novel Inflammatory-Related Gene Signature Based Model for Risk Stratification and Prognosis Prediction in Lung Adenocarcinoma.

Inflammation is an important hallmark of cancer and plays a role in both neogenesis and tumor development. Despite this, inflammatory-related genes (IRGs) remain to be poorly studied in lung adenocarcinoma (LUAD). We aim to explore the prognostic value of IRGs for LUAD and construct an IRG-based prognosis signature. The transcriptomic profiles and clinicopathological information of patients with LUAD were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression were applied in the TCGA set to generate an IRG risk signature. LUAD cases with from the GSE31210 and GSE30219 datasets were used to validate the predictive ability of the signature. Analysis of the TCGA cohort revealed a five-IRG risk signature consisting of EREG, GPC3, IL7R, LAMP3, and NMUR1. This signature was used to divide patients into two risk groups with different survival rates. Multivariate Cox regression analysis verified that the risk score from the five-IRG signature negatively correlated with patient outcome. A nomogram was developed using the IRG risk signature and stage, with C-index values of 0.687 (95% CI: 0.644–0.730) in the TCGA training cohort, 0.678 (95% CI: 0.586–0.771) in GSE30219 cohort, and 0.656 (95% CI: 0.571–0.740) in GSE30219 cohort. Calibration curves were consistent between the actual and the predicted overall survival. The immune infiltration analysis in the TCGA training cohort and two GEO validation cohorts showed a distinctly differentiated immune cell infiltration landscape between the two risk groups. The IRG risk signature for LUAD can be used to predict patient prognosis and guide individual treatment. This risk signature is also a potential biomarker of immunotherapy.

A narrative review of ERBB2 in non-small cell lung carcinoma

The plethora of biomarkers and the availability of targeted treatment have revolutionized the therapeutic profile of non-small cell lung cancer (NSCLC). Erythroblastic oncogene B (ERBB2) has been reported in 1%–4% cases of lung adenocarcinoma and recognized as a prognostic marker in a myriad of cancers like pancreatic, gastric, and breast carcinomas. It is more commonly recognized as human epidermal growth factor receptor 2 (HER2). Molecular characterization of NSCLC based on the mechanism of HER2 activation, including mutation, amplification, and overexpression, has recently been widely adopted owing to the differences in prognosis and predictive outcomes. This narrative review of ERBB2 is intended to describe the molecular biology, historical perspective, clinical profile, and therapeutic options for HER2-activated NSCLC. For the purpose of this review, we performed a comprehensive and detailed search in PubMed, Scopus, and My Cancer Genome databases using the keywords “HER2/neu,” “HER2,” “NSCLC,” “pertuzumab,” “trastuzumab,” and “T-DM1.” A total of 59 articles were included in the review.

Programmed Death Ligand 1 Expression in Lung Adenocarcinoma: An Analysis of the Histomorphological Features.

Immunotherapy is now a vital target therapy in the advanced cases of lung adenocarcinoma. The outstanding result of therapies with medications that inhibit the interaction of programmed death ligand 1 with programmed death protein 1 has revolutionarized prognostic treatment regimes. The study was undertaken with the objectives to analyze the detailed histomorphological features of adenocarcinoma lung with programmed death ligand-1 (PD-L1) expression in tumor cells and to compare the histomorphological features with PD-L1 negative group. The present study is a retrospective case series with 100 cases of non-small cell lung cancer-adenocarcinoma phenotype in which testing for PD-L1 had been done using immunohistochemistry. Detailed histomorphological analysis and comparison was performed for both the PD-L1 positive and negative phenotype. Histomorphological features of 25 cases with positive PD-L1 positivity in the tumor cells and 75 cases that were negative for PD-L1 were analyzed. The most frequent pattern in the category that was PD-L1 positive was singly scattered cells or loose clusters present in 84% cases followed by solid nests that was identified in 60% cases. The presence of solid nests in the PD-L1 positive category was statistically significant (P = 0.018). Mucin was identified in 24% cases, and tumor necrosis was documented in 60% cases with PD-L1 positivity. In the cluster that was PD-L1 positive, 92% cases had moderate-to-severe nuclear pleomorphism. The identification of histomorphological patterns and characteristics may aid in triaging cases that have the likelihood to harbor PD-L1-positive phenotype, which has predictive and prognostic outcome.

Acute Enteric Eosinophilic Myenteric Ganglionitis: A challenging and uncommon case of lung adenocarcinoma

Acute Enteric Eosinophilic Myenteric Ganglionitis: A challenging and uncommon case of lung adenocarcinoma

Development and Validation of a Combined Hypoxia and Immune Prognostic Classifier for Lung Adenocarcinoma.

Lung cancer is the leading cause of cancer-related deaths worldwide. Hypoxia is a crucial microenvironmental factor in lung adenocarcinoma (LUAD). However, the prognostic value based on hypoxia and immune in LUAD remains to be further clarified. The hypoxia-related genes (HRGs) and immune-related genes (IRGs) were downloaded from the public database. The RNA-seq expression and matched complete clinical data for LUAD were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to model construction. Hypoxia expression profiles, immune cell infiltration, functional enrichment analysis, Tumor Immune Dysfunction and Exclusion (TIDE) score and the somatic mutation status were analyzed and compared based on the model. Moreover, immunofluorescence (IF) staining in human LUAD cases to explore the expression of hypoxia marker and immune checkpoint. A prognostic model of 9 genes was established, which can divide patients into two subgroups. There were obvious differences in hypoxia and immune characteristics in the two groups, the group with high-risk score value showed significantly high expression of hypoxia genes and programmed death ligand-1 (PD-L1), and maybe more sensitive to immunotherapy. Patients in the high-risk group had shorter overall survival (OS). This model has a good predictive value for the prognosis of LUAD. We constructed a new HRGs and IRGs model for prognostic prediction of LUAD. This model may benefit future immunotherapy for LUAD.

CCL20 promotes lung adenocarcinoma progression by driving epithelial-mesenchymal transition

C-C motif chemokine ligand 20 (CCL20) participates in multiple oncogenic processes, but its role in lung adenocarcinoma (LUAD) is unclear. Herein, we explored the mechanism by which CCL20 works in LUAD progression. We performed bioinformatical analyses based on the complete transcriptome sequencing data from 1544 LUAD cases in 4 independent cohorts to evaluate signaling pathways regulated by CCL20. We established A549 and H358 cell lines with CCL20 knockdown to explore how CCL20 promotes tumor progression in vitro and in vivo experiments. Using another independent cohort of 348 urothelial carcinoma patients treated with the anti-PD-L1 agent (atezolizumab), we explored the synergistic effect of CCL20 and TGF-β on immunotherapy efficacy. High CCL20 expression is a poor prognostic marker for LUAD patients, and is associated with enhanced epithelial-mesenchymal transition (EMT), inflammatory response, and activated TNF pathway in LUAD. CCL20 knockdown restrained the EMT process and cell proliferation of LUAD cells in vitro and in vivo. Low CCL20 expression blocked the detrimental effects of high TGF-β on survival and effectively improved patients' response to anti-PD-L1 therapy. Collectively, we revealed the underlying mechanisms by which CCL20 promotes LUAD progression based on the largest sample size. The synergistic inhibitory effect of CCL20 and TGF-β on immune-checkpoint blockade therapy efficacy provides new views of immunotherapy resistance.

LINC00628 is differentially expressed between lung adenocarcinoma and squamous cell carcinoma and is associated with the prognosis of NSCLC.

Non-small cell lung cancer (NSCLC) remains the most frequent malignancy worldwide, and lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) represent two major subtypes. LINC00628 has been demonstrated to promote LUAD progression; however, its clinical role in NSCLC remains elusive. The aim of the present study was to analyze the expression of long intergenic non-protein coding RNA 628 (LINC00628) in NSCLC, including in the LUAD and LUSC subtypes. In addition, its roles in NSCLC development and prognosis were also examined. Data from The Cancer Genome Atlas (TCGA) database were first used to assess the expression and prognostic potential in both LUAD and LUSC, then LINC00628 expression in 128 NSCLC tissues was measured using reverse transcription-quantitative PCR. A receiver operating characteristic curve was used to assess the ability of LINC00628 to discriminate between patients with LUAD and LUSC. Kaplan-Meier curves were used to analyze the relationship between LINC00628 expression and the overall survival of patients. Cox regression analysis was used to explore the potential prognostic factors that might be independently associated with NSCLC overall survival. Both in silico and tissue analysis data indicated that the expression of LINC00628 was significantly upregulated in NSCLC tissue compared with matched normal controls (P<0.001). LINC00628 expression levels were also significantly higher in LUAD cases than in patients with LUSC (P<0.001). In addition, LINC00628 could discriminate LUAD from LUSC cases. The expression of LINC00628 was significantly associated with tumor size (P=0.013), histological type (P=0.009), lymph node metastasis (P=0.021) and TNM stage (P=0.008). Survival analysis based on data from both TCGA and patients included in the present study identified an association between LINC00628 and overall survival in LUAD, but this relationship was not observed in LUSC for TCGA data. Cox regression analysis demonstrated that high LINC00628 expression was associated with poor overall survival in patients with LUAD (P=0.001), but not in patients with LUSC (P=0.088). In conclusion, LINC00628 expression was upregulated in NSCLC and associated with patient prognosis. Patients with LUAD had higher LINC00628 expression levels than those with LUSC, and increased LINC00628 served as an independent prognostic factor in LUAD, but not LUSC.

A Case of Lung Adenocarcinoma with Autoimmune Hemolytic Anemia Developing After Immune Checkpoint Inhibitor Treatment

A Case of Lung Adenocarcinoma with Autoimmune Hemolytic Anemia Developing After Immune Checkpoint Inhibitor Treatment

A Case of Lung Adenocarcinoma with Enteric Features showing Calcification on CT

A Case of Lung Adenocarcinoma with Enteric Features showing Calcification on CT